Abstract: A compressor includes: a compressor body that suctions and compresses a gas to be compressed; heat exchangers that circulate a cooled target inside the heat exchangers to cool the cooled target; a fan that is driven by a fan motor and that sends a cooling gas to the heat exchangers to remove heat; a temperature sensor that detects an initial cooling gas temperature that is a temperature of the cooling gas not having been subject to heat removing for the heat exchangers; and a control unit that is capable of setting an upper limit frequency that is an upper limit for controlling a rotational frequency of the fan motor. The control unit sets the upper limit frequency to a rotational frequency equal to or lower than a frequency at which current at an acceptable current level is supplied to the fan motor, at each of the initial cooling gas temperatures detected by the temperature sensor.

Abstract: A secure joining system is a secure joining system including a plurality of secure computing apparatuses. The plurality of secure computing apparatuses include a first vector joining unit, a first permutation calculation unit, a first vector generation unit, a second vector joining unit, a first permutation application unit, a second vector generation unit, a first inverse permutation application unit, a first vector extraction unit, a second permutation application unit, a third vector generation unit, a second inverse permutation application unit, a second vector extraction unit, a modified second table generation unit, a third permutation application unit, a fourth vector generation unit, a shifting unit, a third inverse permutation application unit, a bit inversion unit, a third vector extraction unit, a modified first table generation unit, a first table joining unit, and a first table formatting unit.

Abstract: A secure strong mapping computing system is a secure joining system including a plurality of secure computing apparatuses. The plurality of secure computing apparatuses include a first vector joining unit 11n, a first permutation calculation unit 12n, a first vector generation unit 13n, a second vector joining unit 14n, a first permutation application unit 15n, a second vector generation unit 16n, a first inverse permutation application unit 17n, and a first vector extraction unit 18n.

Abstract: Provided is a technique for performing statistical processing such as processing for obtaining parameters of logistic regression analysis faster than before. A secure statistical processing system includes a cross tabulation table computing device 2 that performs secure computation on a cross tabulation table in which frequencies are in plain texts while keeping each record concealed; and a statistical processing device 3 that performs predetermined statistical processing using the cross tabulation table in which frequencies are in plain texts. The cross tabulation table computing device 2 may include a plurality of secure computation devices 221, . . . , 22N that perform secure computation on a cross tabulation table in which frequencies are fragments subjected to secret sharing while keeping each record concealed, and a management device 21 that restores the fragments to compute the cross tabulation table in which frequencies are in plain texts.

Abstract: A secret grouping apparatus according to an embodiment is a secret grouping apparatus, which classifies a plurality of elements into one or more groups through secret calculation, includes: an input unit configured to receive, as an input, a target vector in which the plurality of elements are disposed so that elements belonging to a same group are continuous, a group information vector representing a last element in the group, and a classification destination vector representing a classification destination of each of the elements in the group; a detection vector calculation unit configured to calculate a detection vector representing a last element of elements classified into a same classification destination in the group by using the target vector, the group information vector, and the classification destination vector; and a classification unit configured to stably sort the target vector and the detection vector with respect to the classification destination vector to create a target vector after classify

Abstract: A secret decision tree learning device according to an embodiment is a secret decision tree learning device for learning a decision tree by secret calculation, that includes an input unit configured to input a data set composed of a plurality of records including one or more attribute values of explanatory variables and attribute values of objective variables; and a learning unit configured to learn the decision tree by collectively dividing the data set at all nodes included in a hierarchical level, for each of a plurality of hierarchical levels of the decision tree.

Abstract: A parameter estimation device for executing a parameter estimation of a cox proportional hazard model by secure computation comprises: a data storage unit that stores a database having, with respect to each object to be observed, a record including a point of time at which an event was observed, a feature amount of an object to be observed at the point of time, and a state of the object to be observed at the point of time; a calculation unit that, by reading a vector comprising points of time from the database, and sorting the vector, generates a replacement table and a flag indicating a boundary between the points of time, by using the replacement table and the flag, totalizer the feature amounts at the respective points of time while concealing values at the points of time, and performs the parameter estimation on the basis of a result of the totalization; and an output unit that outputs a parameter estimated by the calculation unit.

Abstract: A secure joining system is a secure joining system comprising a plurality of secure computation apparatuses; and the plurality of secure computation apparatuses are provided with vector joining parts 11n, first permutation calculating parts 12n, first permutation applying parts 13n, first vector generating parts 14n, second vector generating parts 15n, bit-flipping parts 16n, second permutation calculating parts 17n, second permutation applying parts 18n, third vector generating parts 19n, inverse permutation applying parts 110n, vector separating parts 111n, third permutation applying parts 112n, attribute value permutating parts 113n and fourth vector generating parts 114n.

Abstract: A secret decision tree test device configured to evaluate a division condition at each of a plurality of nodes of a decision tree when learning of the decision tree is performed by secret calculation, the secret decision tree test device includes a memory; and a processor configured to execute inputting a numerical attribute value vector composed of specific numerical attribute values of items of data included in a data set for learning of the decision tree, a label value vector composed of label values of the items of the data, and a group information vector indicating grouping of the items of the data into the nodes; and calculating, using the numerical attribute value vector, the label value vector, and the group information vector, first to fourth frequencies, to evaluate the division condition using the first to fourth frequencies.

Abstract: A secret decision tree test device configured to evaluate a division condition at each of a plurality of nodes of a decision tree when learning of the decision tree is performed by secret calculation, includes a memory; and a processor configured to execute inputting a category attribute value vector composed of specific category attribute values of items of data included in a data set for learning of the decision tree, a label value vector composed of label values of the items of the data, and a group information vector indicating grouping of the items of the data into the nodes; and calculating, using the category attribute value vector, the label value vector, and the group information vector, first to fourth frequencies, to evaluate the division condition using the first to fourth frequencies.

Abstract: An objective of the present disclosure is to provide: anticancer agents having an immune cell-activating effect, a cytotoxic activity, or an antitumor activity, but having a low effect on non-tumor tissues such as normal tissues and having few side effects; combination therapies using those anticancer agents and other anticancer agents; and pharmaceutical combinations for use in those combination therapies. Anticancer agents expected to be applied to various types of cancers, which have an immune cell-activating effect, a cytotoxic activity, or an antitumor activity while having a low effect on non-tumor tissues such as normal tissues and having few side effects by using as an active ingredient an anti-CD137 antigen-binding molecule of the present disclosure, the binding activity of which to CD137 changes depending on various substances (for example, low molecular weight compounds) in target tissues, are provided.

Abstract: The encrypted data analysis device includes a sorting unit that sorts by [Time Information] and then sorts by [User ID] an encrypted data set group including a plurality of encrypted data sets, each of the plurality of encrypted data sets including a [Location ID], the [User ID], and the [Time Information], an encoding unit that generates a [Flow], and encoding the [Location ID] extracted, and an equal sign determination unit that determines whether a [User ID] and another [User ID] adjacent to each other are equal, and when not equal, replaces a corresponding [Flow] with a [predetermined value that represents invalid].

Abstract: To efficiently determine intermediate data for use with an aggregate function while keeping confidentiality, a bit decomposition unit generates a share of a bit string by bit decomposition and concatenation of key attributes. A group sort generation unit generates a share of a first permutation, which performs a stable sort of the bit string in ascending order. A bit string sorting unit generates a share of a sorted bit string obtained by sorting the bit string with the first permutation. A flag generation unit generates a share of a flag indicating a boundary between groups. A key aggregate sort generation unit generates a share of a second permutation, which performs a stable sort of the negation of the flag in ascending order. A de-duplication unit generates shares of de-duplicated key attributes. A key sorting unit generates shares of sorted key attributes by sorting the de-duplicated key attributes.

Abstract: A server determines an array [[addr]] indicating a storage destination of each piece of data, generates an array of concealed values, and connects the generated array to the array [[addr]] to determine an array [[addr?]]. The server generates a sort permutation [[?1]] for the array, applies the sort permutation [[?1]] to the array [[addr?]], and converts the array [[addr?]] into an array with a sequence composed of first Z elements set to [[i]] followed by ?i elements set to [[B]]. The server generates a sort permutation [[?2]] for the converted array [[addr?]], generates dummy data, imparts the generated dummy data to the concealed data sequence, applies the sort permutations [[?1]] and [[?2]] to the data array imparted with the dummy data, and generates, as a secret hash table, a data sequence obtained by deleting the last N pieces of data from the sorted data array.

Abstract: A secure maximum value computation apparatus includes an initialization unit 1 that sets X?=X, a pair creation unit 2 that creates, from among the X?, one or more pairs such that no element is included in two or more pairs, a determination unit 3 that determines, through secure computation, a secret value that is a larger value among [[xi]]and [[xi]] included in each of the one or more pairs for each of the one or more pairs that are created, a set updating unit 4 that sets, as a new X?, when there is a secret value that is not included in the one or more pairs in the X?, a set including the secret value that is not included in the one or more pairs in the X? and the secret value determined by the determination unit, a control unit 5 that performs a control to repeat the above-described processing operations until |X?|=1 holds, and a flag determination unit 6 that determines a flag [[z(xi)]] (i=1, . . .

Abstract: A secure maximum value computation apparatus, assuming that a set X={[[x1]], [[x2]], . . . , [[xn]]}, includes an output unit 1 that outputs [[x1]] and [[1]] as a maximum secret value [[y]] and a flag [[z(x1)]], respectively, when n=1 holds, a comparison unit 2 that computes a comparison result of which is larger with respect to a predetermined order for each pair {[[xi]], [[xj]]}?X of elements of the X, a flag computation unit 3 that computes whether all comparison results related to each of the [[xi]]s are “large” for each of the [[xi]]s to set a computed value as a flag [[z(xi)]], and a maximum value computation unit 4 that uses the [[z(xi)]] to computes a maximum value [[y]].

Abstract: A Fisher's exact test calculation apparatus includes: a condition storage 1 that has stored therein a condition for determining whether a result of Fisher's exact test corresponding to input is significant or not, the input being frequencies in a summary table; and a calculation unit 2 that obtains the result of Fisher's exact test corresponding to the frequencies in the summary table by inputting the frequencies in the summary table to the condition read from the condition storage 1.

Abstract: A computation apparatus, a method of the same, and a program which perform a secure computation using fixed-point arithmetic, and overflow is unlikely to occur and the occurrence of division by zero can be detected when an odds ratio is calculated. The computation apparatus includes an odds ratio computation unit for obtaining an odds ratio between a first group (a+b) and a second group (c+d) based on four plaintext values a, b, c, and d, by means of secure computation; a zero-division detection unit for determining, by means of secure computation, whether or not at least one of the plaintext values b and c is not zero, and detecting division by zero; and a selection unit for selecting the odds ratio if division by zero is not detected, by means of secure computation.

Abstract: Data is efficiently read from a sequence without a read position being revealed. A secure reading apparatus 1 receives a secret text sequence and a secret text of a read position as input, and outputs an element at the read position of the secret text sequence. A vector creating part (12) creates a vector expressing the read position. A compression computing part (13) repeatedly generates a new secret text sequence in which an inner product of a vector based on the secret text sequence and a vector expressing the read position is set as an element. The reading part (14) outputs the new secret text sequence having the number of elements of one as the element at the read position of the secret text sequence.

Abstract: Data is efficiently read from and written in a sequence without an access position being revealed. A secure reading and writing apparatus (1) receives a read command or a write command as input, and, when the read command is input, outputs a secret text [a[x]] which is an x-th element of a secret text sequence [a], and, when the write command is input, adds the secret text [a[x]] which is the x-th element of the secret text sequence [a], to a secret text [d]. A secure reading part (12) reads the secret text [a[x]] which is the x-th element from the secret text sequence [a]. A buffer addition part (13) adds a secret text [c] of an unreflected value c to the secret text [a[x]]. A buffer appending part (14) appends a secret text [x] and the secret text [d] to a write buffer [b].